code: def _inverse_norm(n_bit=8):  # pragma: no cover
      """
      Generate bin edges from an inverse normal distribution
  
      This distribution is best suited for z-normalized time series data
  
      Parameters
      ----------
      n_bit : int, default 8
          The number of bits to be used in generating the inverse normal distribution
  
      Returns
      -------
      out : numpy.ndarray
          Array of bin edges that can be used for data discretization
      """
      return norm.ppf(np.arange(1, (2**n_bit)) / (2**n_bit))
  
file_path: stumpy/stumpy/mstump.py
imports: from functools import lru_cache, partial
  import numpy
  from numba import njit, prange
  from scipy.stats import norm
  from .None import config, core
  from .maamp import maamp, maamp_mdl, maamp_multi_distance_profile, maamp_subspace
label_desc: Use image node_id 3 for calling a global function with example usage: _inverse_norm(n_bit) and returns: norm